A risk-predictive model for invasive pulmonary aspergillosis in patients with acute exacerbation of chronic obstructive pulmonary disease
Autor: | Jinjin Zhong, Xianping Ye, Yuxiu Liu, Yu Gu, Kunlu Shen, Bilin Chen, Yu Wang, Xin Su |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Male
China Acute exacerbation of chronic obstructive pulmonary disease medicine.medical_specialty Exacerbation Comorbidity Logistic regression Risk Assessment Nomogram Pulmonary Disease Chronic Obstructive 03 medical and health sciences Diseases of the respiratory system 0302 clinical medicine Prednisone Internal medicine medicine Humans 030212 general & internal medicine Aged Retrospective Studies Invasive Pulmonary Aspergillosis COPD AECOPD RC705-779 business.industry Research Incidence (epidemiology) Retrospective cohort study medicine.disease respiratory tract diseases Early Diagnosis 030228 respiratory system Risk factors IPA Disease Progression Female business Follow-Up Studies medicine.drug Model |
Zdroj: | Respiratory Research, Vol 22, Iss 1, Pp 1-9 (2021) Respiratory Research |
Popis: | Objectives Invasive pulmonary aspergillosis (IPA) is increasingly reported in chronic obstructive pulmonary disease (COPD) patients. These patients often have poor clinical outcomes. Early recognition of IPA in COPD is always challenging. We aimed to develop and validate a risk model using readily available clinical parameters to predict IPA for acute exacerbation of COPD (AECOPD) patients. Methods We performed a retrospective cohort study. AECOPD patients who were admitted to Jinling Hospital between January 2012 and December 2017 were included. 880 AECOPD patients were randomly divided into the training set (70%, n = 616) and validation set (30%, n = 264). A nomogram model was developed using multivariate logistic regression from training set. The discrimination and calibration of model were validated internally. Decision curve analyses assessed the clinical utility of the nomogram. Results The incidence of IPA in hospitalized AECOPD patients was 9.6% in the training set (59 cases of IPA) and 9.1% in the validation set (24 cases of IPA), respectively. The nomogram model consisted of independent factors associated with IPA included lung function GOLD III–IV, use of broad-spectrum antibiotic over 10 days in the last month, oral or intravenous corticosteroids (prednisone) over 265 mg in the last 3 months and serum albumin P = 0.887). Conclusion The simple risk predictive model for earlier recognition of IPA is useful in hospitalized AECOPD patients. |
Databáze: | OpenAIRE |
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